The present invention relates to imaging systems and, more particularly, to imaging systems in which perceived depth-of-field can be reduced by digital image processing.
Electronic devices such as cellular telephones are often provided with camera sensors. Users of these devices sometimes desire to capture images having relatively shallow depth of field. The depth of field in an image is the range of distances over which the image appears to be in focus. In an image with a shallow depth of field, only objects that are close to the plane of focus will appear sharp and in focus. Objects in an image with a shallow depth of field image that lie in front of the plane of focus or behind the plane of focus will be blurred. Images with a large depth of field appear sharp over a greater distance. In this type of scenario, even objects that lie significantly off of the plane of focus will appear to be sharp. Users may prefer images with a shallow depth of field for various artistic and functional reasons.
One way to obtain an image with a shallow depth of field involves increasing the aperture of the camera lens. This process can only be used in devices with adjustable-aperture lenses. The use of a large aperture to reduce depth of field may also require the use of a fast exposure time, which may prevent the user from intentionally incorporating motion blur into a captured image.
Another way in which to obtain images with shallow depth of field involves the use of digital image processing to reduce the depth of field of an image. Conventional digital image processing techniques for reducing the depth of field of an image involve blurring regions (i.e., kernels) that are further from the focal plane to a greater extent than regions (i.e., kernels) that are closer to the focal plane. With conventional techniques, the kernel size (e.g., width) becomes larger with increasing distance from the focal plane. As a given kernel increases in size, the total number of pixels within that kernel, all of which need to be processed to blur the given kernel, increases by the approximately the square of the kernel width. The conventional digital image processing techniques are therefore computationally inefficient, expensive, and inappropriate for many applications.